Q-omics provides the consensus-scored HHIPL1 profile across patient tissues and cancer cell-line models. HHIPL1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, HHIPL1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, HHIPL1 RNA expression shows 15,867 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight BLCA, HNSC, and PDAC as cancer lineages where HHIPL1 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for HHIPL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HHIPL1 survival associations across molecular data types. HHIPL1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HHIPL1 RNA expression–survival associations across cancer types. High HHIPL1 expression shows unfavorable associations in BLCA, ACC, BRCA, KIRP and THCA, but favorable associations in LGG. The BLCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify BLCA as the clearest survival context for HHIPL1 RNA expression.
This table summarizes HHIPL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for HHIPL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HHIPL1 shows lower tumor expression in BLCA and KICH and higher tumor expression in HNSC, KIRC, BRCA and THCA. The HNSC box plot shows higher HHIPL1 RNA expression in tumor versus normal tissue (log2 FC = +0.795, t-test p < 0.001).
This table shows molecular features associated with HHIPL1 in patient tissues and cancer cell lines. In patient samples, HHIPL1 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, HHIPL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and LARGE_INTESTINE.
